Model save
Browse files- README.md +65 -0
- config.json.sagemaker-uploaded +0 -0
- generation_config.json +6 -0
- generation_config.json.sagemaker-uploaded +0 -0
- model-00001-of-00003.safetensors.sagemaker-uploading +0 -0
- model-00002-of-00003.safetensors.sagemaker-uploading +0 -0
- model-00003-of-00003.safetensors.sagemaker-uploading +0 -0
- model.safetensors.index.json.sagemaker-uploaded +0 -0
- special_tokens_map.json.sagemaker-uploaded +0 -0
- tokenizer.json.sagemaker-uploaded +0 -0
- tokenizer.model.sagemaker-uploaded +0 -0
- tokenizer_config.json.sagemaker-uploaded +0 -0
- training_args.bin.sagemaker-uploaded +0 -0
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: mistralai/Mistral-7B-v0.1
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tags:
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- llama-factory
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- generated_from_trainer
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model-index:
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- name: checkpoints
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# checkpoints
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1202
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 16
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 1024
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- total_eval_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.509 | 0.9565 | 11 | 1.1202 |
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### Framework versions
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- Transformers 4.45.2
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- Pytorch 2.3.0
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- Datasets 2.21.0
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- Tokenizers 0.20.1
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config.json.sagemaker-uploaded
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"transformers_version": "4.45.2"
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}
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model-00001-of-00003.safetensors.sagemaker-uploading
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special_tokens_map.json.sagemaker-uploaded
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tokenizer.json.sagemaker-uploaded
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tokenizer.model.sagemaker-uploaded
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